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Experimental Comparison of Visual Inspection and Infrared Thermography for the Detection of Soling and Partial Shading in Photovoltaic Arrays

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Smart Cities (ICSC-CITIES 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1359))

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Abstract

Soling and partial shading of solar panels are two of the most common conditions that affects the power yield of a photovoltaic (PV) installation. Even though human inspection can easily identify such situations, in the case of large power plants covering thousands of hectares it is not practical. In this regard, unmanned areal systems (UAS) represents a useful tool to gather images in a short time for the inspection of thousands of PV panels. Using RGB and infrared cameras, UAS can be used to perform visual inspection (VI) and infrared thermography (IRT) to detect failures in PV arrays. The present paper presents the results of an experiment designed to evaluate the effectiveness of VI and IRT for detecting soiling and partial shadowing. It has been found that for the aforementioned conditions VI are more effective. Also, the methodology presented can be used as a reference for future research for other techniques and other failures. The results provide technical-scientific information for those in charge of operation and maintenance to make an objective choice of failure detection techniques.

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References

  1. Acciani, G., Falcone, O., Vergura, S.: Typical defects of PV-cells. In: IEEE International Symposium on Industrial Electronics, pp. 2745–2749 (2010). https://doi.org/10.1109/ISIE.2010.5636901

  2. Alsafasfeh, M., Abdel-Qader, I., Bazuin, B.: Fault detection in photovoltaic system using SLIC and thermal images. In: 2017 8th International Conference on Information Technology (ICIT). IEEE, May 2017. https://doi.org/10.1109/icitech.2017.8079925

  3. Bolboacă, S.D., Jäntschi, L., Sestraş, A.F., Sestraş, R.E., Pamfil, D.C.: Pearson-fisher chi-square statistic revisited. Information 2(3), 528–545, September 2011. https://doi.org/10.3390/info2030528

  4. Cardinale-Villalobos, L., Rimolo-Donadio, R., Meza, C.: Solar panel failure detection by infrared UAS digital photogrammetry: a case study. Int. J. Renew. Energy Res. (IJRER) 10(3), 1154–1164 (2020)

    Google Scholar 

  5. Chaudhary, A.S., Chaturvedi, D.: Thermal image analysis and segmentation to study temperature effects of cement and bird deposition on surface of solar panels. Int. J. Image Graph. Sig. Process. 9(12), 12–22 (2017). https://doi.org/10.5815/ijigsp.2017.12.02

    Article  Google Scholar 

  6. Cohen, H.W.: P values: use and misuse in medical literature. Am. J. Hypertens. 24(1), 18–23, January 2011. https://doi.org/10.1038/ajh.2010.205

  7. Cubukcu, M., Akanalci, A.: Real-time inspection and determination methods of faults on photovoltaic power systems by thermal imaging in turkey. Renew. Energy 147, 1231–1238, March 2020. https://doi.org/10.1016/j.renene.2019.09.075

  8. Felipe-García, B., Hernández-López, D., Lerma, J.L.: Analysis of the ground sample distance on large photogrammetric surveys. Appl. Geomatics 4(4), 231–244 (2012). https://doi.org/10.1007/s12518-012-0084-2

    Article  Google Scholar 

  9. FLIR: A guide to inspecting solar fields with thermal imaging drones (2019). https://thermalcapture.com/wp-content/uploads/2019/08/pv-system-inspection-thermal-drones-07-15-19.pdf

  10. Flir: Flir Vue Pro and Flir Vue Pro R (2019). http://www.flir-vue-pro.com/wp-content/uploads/2016/10/FLIR-VUE-Pro-R-Datasheet-TeAx.pdf

  11. Flir.com: Adjusting Sensitivity and Gain On The FLIR Vue Pro R (2019). https://flir.custhelp.com/app/answers/detail/a_id/3134

  12. Gallardo-Saavedra, S., Hernandez-Callejo, L., Duque-Perez, O.: Image resolution influence in aerial thermographic inspections of photovoltaic plants. IEEE Trans. Ind. Inf. 14(12), 5678–5686, December 2018. https://doi.org/10.1109/tii.2018.2865403

  13. Gutiérreza-Pulido, H., De la Vara-Salazar, R.: Análisis y diseño de experimentos, 2nd edn. McGraw-Hill Interamericana, México D.F. (2008)

    Google Scholar 

  14. Hernández Sampieri, R., Fernández Collado, C., Baptista, L., Del Pilar, M.: Metodología de la investigación, 5th edn. Mc Graw Hill, México (2010)

    Google Scholar 

  15. Higuchi, Y., Babasaki, T.: Failure detection of solar panels using thermographic images captured by drone. In: 2018 7th International Conference on Renewable Energy Research and Applications (ICRERA). IEEE, October 2018. https://doi.org/10.1109/icrera.2018.8566833

  16. International Energy Agency: Review of Failures of Photovoltaic Modules. Technical Report July, Performance and Reliability of Photovoltaic Systems (2014)

    Google Scholar 

  17. International Energy Agency: Review on Infrared and Electroluminescence Imaging for PV Field Applications. Technical Report, Photovoltaic Power Systems Programme (2018)

    Google Scholar 

  18. Javed, W., Wubulikasimu, Y., Figgis, B., Guo, B.: Characterization of dust accumulated on photovoltaic panels in Doha, Qatar. Solar Energy 142, 123–135, January 2017. https://doi.org/10.1016/j.solener.2016.11.053

  19. Jones, J.B., Schropp, M.A.: Research fundamentals: statistical considerations in research design: a simple person’s approach. Acad. Emerg. Med. 7(2), 194–199 (2000). https://doi.org/10.1111/j.1553-2712.2000.tb00529.x

    Article  Google Scholar 

  20. Leva, S., Aghaei, M., Grimaccia, F.: PV power plant inspection by UAS: correlation between altitude and detection of defects on PV modules. In: 2015 IEEE 15th International Conference on Environment and Electrical Engineering (EEEIC). IEEE, June 2015. https://doi.org/10.1109/eeeic.2015.7165466

  21. Linder, W.: Introduction. Digital Photogrammetry, 4th edn., pp. 10–12. Springer-Verlag, Berlin (2016). https://doi.org/10.1007/978-3-662-50463-5

    Chapter  Google Scholar 

  22. Köntges, M.: Reviewing the practicality and utility of electroluminescence and thermography (2014). https://www.nrel.gov/pv/assets/pdfs/2014_pvmrw_33_kontges.pdf

  23. Madeti, S.R., Singh, S.: A comprehensive study on different types of faults and detection techniques for solar photovoltaic system. Solar Energy 158, 161–185, December 2017. https://doi.org/10.1016/j.solener.2017.08.069

  24. Maghami, M.R., Hizam, H., Gomes, C., Radzi, M.A., Rezadad, M.I., Hajighorbani, S.: Power loss due to soiling on solar panel: a review. Renew. Sustain. Energy Rev. 59, 1307–1316, June 2016. https://doi.org/10.1016/j.rser.2016.01.044

  25. Mchugh, M.L.: The odds ratio: calculation, usage, and interpretation. Biochemia medica 19(2), 120–126 (2009). https://hrcak.srce.hr/37593

  26. Mekki, H., Mellit, A., Salhi, H.: Artificial neural network-based modelling and fault detection of partial shaded photovoltaic modules. Simul. Model. Pract. Theory 67, 1–13, September 2016. https://doi.org/10.1016/j.simpat.2016.05.005

  27. Mellit, A., Tina, G., Kalogirou, S.: Fault detection and diagnosis methods for photovoltaic systems: a review. Renew. Sustain. Energy Rev. 91, 1–17, August 2018. https://doi.org/10.1016/j.rser.2018.03.062

  28. Moretón, R., Lorenzo, E., Narvarte, L.: Experimental observations on hot-spots and derived acceptance/rejection criteria. Solar Energy 118, 28–40, August 2015. https://doi.org/10.1016/j.solener.2015.05.009

  29. Murillo-Soto, L., Meza, C.: Fault detection in solar arrays based on an efficiency threshold. In: 2020 IEEE 11th Latin American Symposium on Circuits Systems (LASCAS), pp. 1–4 (2020). https://doi.org/10.1109/LASCAS45839.2020.9069046

  30. Murillo-Soto, L.D., Meza, C.: Photovoltaic array fault detection algorithm based on least significant difference test. In: Figueroa-García, J.C., Garay-Rairán, F.S., Hernández-Pérez, G.J., Díaz-Gutierrez, Y. (eds.) WEA 2020. CCIS, vol. 1274, pp. 501–515. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-61834-6_43

    Chapter  Google Scholar 

  31. Mäki, A., Valkealahti, S.: Power losses in long string and parallel-connected short strings of series-connected silicon-based photovoltaic modules due to partial shading conditions. IEEE Trans. Energy Convers. 27(1), 173–183, March 2012. https://doi.org/10.1109/tec.2011.2175928

  32. National Renewable Energy Laboratory: Development of a Visual Inspection Data Collection Tool for Evaluation of Fielded PV Module Condition (2012). https://doi.org/10.2172/1050110, http://www.osti.gov/bridge

  33. Pintea, S., Moldovan, R.: The receiver-operating characteristic (ROC) analysis: fundamentals and applications in clinical psychology. J. Cogn. Behav. Psychotherapies 9(1), 49–66 (2009)

    Google Scholar 

  34. Sisodia, A.K., Mathur, R.: Impact of bird dropping deposition on solar photovoltaic module performance: a systematic study in Western Rajasthan. Environ. Sci. Pollution Res. 26(30), 31119–31132 (2019). https://doi.org/10.1007/s11356-019-06100-2

    Article  Google Scholar 

  35. Tango, T.: Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials. Taylor & Francis Group, Tokyo, Japan (2017)

    Book  Google Scholar 

  36. Tsanakas, J.A., Ha, L., Buerhop, C.: Faults and infrared thermographic diagnosis in operating CSI photovoltaic modules: a review of research and future challenges. Renew. Sustain. Energy Rev. 62, 695–709, September 2016. https://doi.org/10.1016/j.rser.2016.04.079

  37. Tyutyundzhiev, N., Lovchinov, K., Martínez-Moreno, F., Leloux, J., Narvarte, L.: Advanced PV modules inspection using multirotor UAV. In: 31st European Photovoltaic Solar Energy Conference and Exhibition, Hamburg (2015). https://www.researchgate.net/publication/283087341

  38. Watson, J.J., Hudson, M.D.: Regional scale wind farm and solar farm suitability assessment using GIS-assisted multi-criteria evaluation. Landscape Urban Plan. 138, 20–31, June 2015. https://doi.org/10.1016/j.landurbplan.2015.02.001

  39. Wohlin, C., Runeson, P., Höst, M., Ohlsson, M.C., Regnell, B., Wesslén, A.: Experimentation in Software Engineering. Springer, New York (2012). https://doi.org/10.1007/978-3-642-29044-2

  40. Zefri, Y., ElKettani, A., Sebari, I., Lamallam, S.A.: Thermal infrared and visual inspection of photovoltaic installations by UAV photogrammetry—application case: Morocco. Drones 2(4), 41, November 2018. https://doi.org/10.3390/drones2040041

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Acknowledgement

This paper is part of a project 5402-1360-4201 “Identificación de Fallas en Sistemas Fotovoltaicos” financed by the Costa Rica Institute of Technology. In addition, the first author is part of the Master of Science: Maestría en Ciencia y Tecnología para la Sostenibilidad of DOCINADE. Thanks to the Electronics students at TEC Dalberth Alberto Corrales Alpizar and Jose Eduardo Zuñiga Ramirez for their contribution in the development of the data acquisition system and John Martin Chacon Zambrana for the support in the data collection of the experiment.

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Authors and Affiliations

  1. Electronics Engineering School, Instituto Tecnológico de Costa Rica, Cartago, Costa Rica

    Leonardo Cardinale-Villalobos & Carlos Meza

  2. Electromechanic Engineering School, Instituto Tecnológico de Costa Rica, Cartago, Costa Rica

    Luis D. Murillo-Soto

Authors
  1. Leonardo Cardinale-Villalobos
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  2. Carlos Meza
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  3. Luis D. Murillo-Soto
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Correspondence to Leonardo Cardinale-Villalobos .

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Editors and Affiliations

  1. Universidad de la República, Montevideo, Uruguay

    Sergio Nesmachnow

  2. University of Valladolid, Soria, Spain

    Luis Hernández Callejo

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Cardinale-Villalobos, L., Meza, C., Murillo-Soto, L.D. (2021). Experimental Comparison of Visual Inspection and Infrared Thermography for the Detection of Soling and Partial Shading in Photovoltaic Arrays. In: Nesmachnow, S., Hernández Callejo, L. (eds) Smart Cities. ICSC-CITIES 2020. Communications in Computer and Information Science, vol 1359. Springer, Cham. https://doi.org/10.1007/978-3-030-69136-3_21

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  • DOI: https://doi.org/10.1007/978-3-030-69136-3_21

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